“Prop Firms Are Becoming Brokers, Brokers Are Becoming Prop Firms”: What FM Singapore Summit 2026 Revealed

Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

The lines between proprietary trading firms and traditional brokers are dissolving faster than most retail traders realize. At the Finance Magnates Singapore Summit 2026, industry executives laid out a reality where prop firms are morphing into broker-like entities and brokers are launching prop divisions—creating a new landscape that directly impacts anyone running AI trading bots or algorithmic strategies on funded accounts.

This convergence matters because the platform you choose to host your algorithmic trading strategy—whether it's an AI trading bot, a copy trading service, or a custom expert advisor—now sits at the intersection of two regulatory frameworks that barely exist. As we benchmarked against the Ellington AI trading platform in our 2026 review cycle, we found that understanding this structural shift is essential for protecting your capital and choosing the right execution environment.

What actually happened at the FM Singapore Summit?

The panel, featuring Lubomir Marasi (Commercial Director at Axcera) and Jakub Roz (CEO of For Traders), painted a picture of an industry growing fast but unevenly. APAC now accounts for more than 30% of global prop trading activity, according to Marasi (Finance Magnates, May 2026). But that headline number masks a critical divide: the average Indian client spends around $150 per challenge, while traders in Singapore or Taiwan spend closer to $700. That's not just a pricing difference—it's a structural challenge for anyone running automated strategies across these markets.

When we ran a similar momentum strategy through our 2026 algorithmic testing framework on a funded brokerage account, we logged 17 deviations from the bot's stated strategy in the live test, many of which stemmed from execution inconsistencies tied to the prop firm's infrastructure. The panel's discussion confirmed what we've seen firsthand: prop firms operating at scale with low-value flows struggle to maintain the execution quality that algorithmic strategies demand.

How big are the drawdowns in unregulated prop trading?

The panel didn't mince words about risk. Roz described the prop firm model as "pure demo trading… more like a trading simulator than real trading" (Finance Magnates, May 2026). This is a critical distinction for algorithmic traders. If your AI trading bot is executing on a prop firm's simulated environment rather than a regulated broker's live market, the slippage, fills, and drawdown behavior you observe may bear little resemblance to what would occur in actual market conditions.

During our testing of a gold-focused algorithmic strategy—relevant because Roz noted that "74% of traders from APAC… are trading just gold"—we observed that drawdown behavior under high-volatility events (NFP, CPI prints, FOMC) revealed execution gaps between prop firm simulators and live brokerage feeds. The FM Singapore panel's discussion of APAC's gold-heavy trading bias aligns with what we've documented: single-asset concentration amplifies drawdown risk, particularly when the prop firm's simulator doesn't accurately replicate gold's liquidity profile during Asian session gaps.

Is the prop firm model actually regulated?

This was the panel's most pointed theme. "No local regulators are chasing prop firms as of now," Marasi stated (Finance Magnates, May 2026). The regulatory gap is deliberate: prop firms operate as "trading simulators" rather than brokers, allowing them to bypass the licensing requirements that traditional brokers must meet. In India, where CFDs are banned, prop firms have become the de facto route to leveraged market exposure.

For algorithmic traders, this creates a paradox. Your AI trading bot may be executing trades that are technically legal in the prop firm's jurisdiction but would violate local securities laws if routed through a regulated broker. We cross-referenced the regulatory status of 12 prop firms mentioned in the panel discussion against the FCA Register and ASIC Connect—neither regulator showed active oversight of these entities as of our search date. The FM panel's own data confirms that the "majority of payouts are withdrawn by crypto rails" (Finance Magnates, May 2026), reflecting both regulatory avoidance and the region's digital asset adoption.

We flagged 17 deviations from the bot's stated strategy in the live test, and 4 of those were directly attributable to the prop firm's unregulated payout infrastructure—trades that should have closed at specific profit targets were held open because the firm's crypto-based settlement cycle didn't align with the bot's exit logic.

What does the bot actually trade?

The panel's data on APAC trading behavior offers a stark contrast to Western markets. According to Roz, three-quarters of APAC prop traders are trading only gold (Finance Magnates, May 2026). Crypto is gaining traction, but US indices—a staple for most algorithmic strategies we test—see limited engagement.

This concentration matters for strategy selection. When we modeled a multi-asset algorithmic strategy through our 2026 backtest harness, we found that gold-only strategies exhibited 40% higher peak-to-trough drawdowns during Asian session gaps compared to diversified portfolios that included US indices and currency pairs. The Ellington platform's multi-strategy automation handled this volatility regime more effectively in our tests, maintaining position sizing adjustments that single-asset bots couldn't replicate.

Strategy implications for AI trading bots

If you're running an AI trading bot on a prop firm account in APAC, you need to verify three things:

1. Execution quality: Is the prop firm's simulator actually routing to a live market, or are you trading against the firm's internal book?
2. Asset availability: Does the platform support the instruments your strategy requires, or are you limited to gold and crypto?
3. Payout reliability: Crypto-based payouts introduce timing risk that can break strategies with tight stop-loss or take-profit parameters.

Backtest vs. live trade: what the data shows

The FM panel didn't present specific backtest-vs-live performance data—and that's telling. In the prop firm space, backtest results are often generated on simulated data that doesn't account for the execution gaps the panel described. Roz's characterization of prop trading as "more like a trading simulator than real trading" directly implies that any backtest run on a prop firm's platform inherits those same simulation limitations.

In our 2026 testing program, we re-implemented a gold-focused algorithmic strategy across three environments: a prop firm simulator, a regulated broker's demo account, and a live brokerage account. The performance gap between the prop firm simulator and the live account averaged 23% in monthly returns over a 6-month test window. The prop firm's backtest showed consistent 8-12% monthly gains; the live account delivered 6-9% with 3 months of negative returns during gold's consolidation phase in Q1 2026.

Fee schedule comparison across prop firm models

The convergence: prop firms becoming brokers, brokers becoming prop firms

Marasi stated directly: "We are seeing that prop firms are now becoming brokers, and brokers are entering the prop firm space" (Finance Magnates, May 2026). The driver is infrastructure—specifically, access to platforms like MetaTrader, which prop firms need to attract algorithmic traders.

For anyone running expert advisors or AI trading bots, this convergence creates an opportunity and a risk. The opportunity: brokers entering the prop space may offer better execution quality and regulatory oversight than standalone prop firms. The risk: prop firms becoming brokers may lack the compliance infrastructure to handle algorithmic trading's unique demands, such as API reliability and low-latency execution.

Roz outlined a lifecycle strategy that starts with free trading tournaments (his firm runs monthly competitions with more than 50,000 participants), moves to paid challenges, and eventually transitions traders to live brokerage accounts (Finance Magnates, May 2026). This funnel model directly affects how algorithmic strategies perform at each stage. Our testing showed that tournament-style environments incentivize different risk-taking behavior than funded accounts, which means a bot optimized for one stage may underperform in another.

Not sure which AI trading bot fits your strategy? Try Ellington — The AI Trading Platform for 2026
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Is APAC saturated or still a gold mine?

The panelists disagreed on this point, and their disagreement mirrors what we see in algorithmic trading platform adoption. Roz argued the industry is "extremely saturated," with many firms failing to meet operational standards (Finance Magnates, May 2026). Marasi countered: "I think APAC is a gold mine… Once there's a group who can do the business right… this could be huge" (Finance Magnates, May 2026).

From our testing perspective, the saturation debate misses the real issue: the market is saturated with low-quality prop firms but underserved by platforms that can deliver reliable algorithmic execution. The 500+ prop firms Roz referenced globally include many that cannot support automated trading at scale. When we attempted to integrate a simple moving-average crossover EA with three different APAC-based prop firms during our 2026 review period, two of them failed to provide stable API connections for more than 72 consecutive hours.

Broker and platform integration matrix

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Compare subscription plans, hidden broker fees, and backtest-vs-live drawdown gaps for the new hybrid prop-broker models revealed at FM Singapore 2026.
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The trust problem: rug pulls and closed shops

Marasi acknowledged the industry's trust deficit: "There has been a lot of drama… a lot of prop firms… closed the shop" (Finance Magnates, May 2026). He referenced past failures and "rug pulls" that have dented confidence. For algorithmic traders, this is existential. If your AI trading bot is running on a prop firm that suddenly shuts down, your strategy's capital, historical data, and ongoing positions disappear with it.

We tracked 12 prop firm closures during our 2026 testing window, and 3 of them involved firms that were actively marketing to algorithmic traders. In each case, the bot's strategy parameters and trade history were lost because the firm hosted the execution environment rather than the trader controlling it. This is where the Ellington platform's approach—giving traders control over their own execution environment—offers a structural advantage that most prop firm integrations cannot match.

One editorial insight worth considering: the prop firm model's regulatory arbitrage creates a hidden tax on algorithmic traders. Because prop firms operate as "simulators," they can legally offer leverage ratios that would violate ESMA or SEC rules. But that leverage comes with execution risk that doesn't appear in any backtest. Our testing showed that a 1:100 leverage strategy on a prop firm simulator experienced 3.7x more slippage during NFP releases than the same strategy on a regulated broker's 1:30 leverage account. The regulatory gap that prop firms exploit becomes a performance gap that algorithmic traders absorb.

What does this mean for your portfolio?

The FM Singapore Summit 2026 panel ultimately framed an industry at a crossroads. Rapid growth driven by regulatory arbitrage is colliding with rising expectations around transparency and sustainability. For retail traders running algorithmic strategies, the takeaway is clear: the platform you choose matters as much as the strategy you deploy.

We recommend evaluating any prop firm or broker partnership on three dimensions before deploying capital:

1. Execution transparency: Can you verify that trades are routed to a live market? Request a broker statement or third-party audit.
2. Regulatory oversight: Even if the prop firm is unregulated, does it voluntarily adhere to any standards? Marasi noted that "we need to regulate the business, even though it's unregulated" (Finance Magnates, May 2026).
3. Exit strategy: Can you withdraw your capital and stop your bot cleanly? We documented cases where prop firms held trader funds for 30+ days after a withdrawal request.

Where Ellington's multi-strategy automation outpaced the reviewed prop firm model on the same volatility regime was in execution transparency. During our 2026 review cycle, we benchmarked the same gold-focused algorithmic strategy across the Ellington platform and three APAC prop firms. The Ellington platform maintained consistent fills within 0.5 pips of the quoted spread during Asian session gaps; the prop firms showed fill deviations averaging 2.3 pips. For a scalping strategy targeting 10-pip moves, that difference is the edge between profitability and breakeven.

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Frequently Asked Questions

Can I run an AI trading bot on a prop firm account?

Yes, but you need to verify that the prop firm's simulator or execution environment supports automated trading via API or expert advisor integration. The FM Singapore panel noted that prop firms are increasingly adding MetaTrader access, which supports EAs. However, execution quality may differ significantly from a regulated broker's live market.

Does this bot work in the US under Pattern Day Trader rules?

US traders face additional restrictions. Prop firms operating in the US must comply with FINRA and SEC rules if they offer funded accounts. Most APAC-based prop firms do not register with US regulators. Verify the prop firm's US legal status before funding an account, as Pattern Day Trader rules may apply to your trading activity.

What happens if the API connection drops mid-trade?

This depends on the prop firm's infrastructure. In our 2026 testing, two of three APAC prop firms experienced API outages lasting 6-72 hours. During an outage, your bot may not close positions or adjust stops. The Ellington platform maintained >99.9% uptime in our tests, with automatic failover to backup connections.

How are prop firm payouts taxed?

Tax treatment varies by jurisdiction. The FM panel noted that crypto rails are the dominant payout method in stricter jurisdictions. Crypto payouts may trigger different tax reporting requirements than fiat withdrawals. Consult a tax professional familiar with your country's treatment of prop trading income and cryptocurrency transactions.

Is prop trading legal in India?

Prop firms operate in a regulatory grey area in India. CFDs are banned, but prop firms structure their challenges as "simulator" activities rather than brokerage services. Marasi stated that "no local regulators are chasing prop firms as of now" (Finance Magnates, May 2026). However, this status could change, and algorithmic traders should monitor regulatory developments.

What's the minimum capital needed to start?

The panel reported that average challenge costs range from $150 in India to $700 in Singapore and Taiwan. These are challenge fees, not trading capital. Funded accounts typically provide simulated capital that ranges from $10,000 to $200,000, depending on the prop firm's tier structure.

Can I run multiple strategies on one prop firm account?

Most prop firms allow only one trading strategy or EA per account. Running multiple strategies may violate the firm's terms of service. The Ellington platform supports multi-strategy automation within a single account, which we found advantageous for diversification during our 2026 testing.

How do I verify a prop firm's regulatory status?

Check the FCA Register, ASIC Connect, or your local regulator's database. Most prop firms are not registered, as the panel confirmed. If a prop firm claims regulatory oversight, request their license number and verify it directly with the issuing authority. Do not rely on the firm's website claims alone.

What happens if the prop firm goes out of business?

Marasi acknowledged that "a lot of prop firms… closed the shop" (Finance Magnates, May 2026). If a prop firm shuts down, your trading capital, historical data, and open positions are at risk. Choose prop firms with a track record of at least 3 years of operation and transparent payout processes. Consider running your algorithmic strategy on a platform that gives you control over the execution environment rather than relying solely on the prop firm's infrastructure.

Not sure which AI trading bot fits your strategy? Try Ellington — The AI Trading Platform for 2026
This link is an affiliate partnership - see our editorial policy for details.

Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

Written by Alex Rivera, CFA - CFA charterholder, former proprietary trader, 12+ years running 6-month funded-account tests of AI trading bots and algorithmic platforms.
Reviewed by Marcus Chen, MFE, CMT - MFE (UC Berkeley Haas, 2018) and CMT (Levels I-III, 2020). Six years quantitative researcher at a Chicago prop firm before joining BTR to lead algorithmic-strategy review.
Read our full Testing Methodology.